Probability of success

Probability of success
See also

Probability of success is one of the key management decision factors closely related to the same concept described in statistics and probability theory. Probability of success is derived from data gathered by researches and market analysis during identification of threats and opportunities for important development decision (entering new market, new product preparation, etc.).

The impact of working in multicultural teams on success[edit]

Global enterprises are very numerous and what is important, they employ people from different cultures. employees arrivals from culturally diverse countries are characterized by some common features, but also have some differences. In front of the management of these companies is a great challenge to integrate these culturally diverse employees in order to ensure their efficient functioning in the organization. The creation of such a team requires both the superior and colleagues learning about cultures, identifying differences and similarities in the approach to tasks. Creating an effective team multiculturalism is a big confession that is worth taking, because it gives many benefits to organizations.[1]

Mathematical methods to calculate the probability of success[edit]

Bernoulli attempt is an experience in which we get one of two possible outcomes. One of these results is called success and the other a failure. If the probability of success is \( p \), then the probability of failure is \( q=1-p \).[2]

Bernoulli scheme is called a sequence of independent repetitions of Bernoulli attempt.

In the Bernoulli scheme, obtaining exactly \( k \) successes in \( n \) attempts can be calculated from the formula:[3]

\( P_{n} (k)= \binom{n}{k} p^k q^{n-k}, \)

Example: We throw the dice three times. What is the probability that 4 will fall out twice?

\( n=3 \) the number of throws

\( k=2 \) number of successes (falling 4)

\( p=\frac{1}{6} \) the probability of success (falling 5)

\( q=1-\frac{1}{6}=\frac{5}{6} \) probability of failure (5 failed)

\( P_{3} (2) = \binom{3}{2} (\frac{1}{6})^{2} (\frac{5}{6})^{3-2} = \frac{5}{72}, \)

The probability that in three throws 5 will be exactly two times is \( \frac{5}{72} \).


  1. Zander L., Butler C. L. (2010).
  2. Borovkov A. (1998).
  3. Borovkov A. (1998).


Author: Klaudia Wróbel